用于管道漏磁数据的小波域自适应及小波系数去噪算法

基于漏磁检测是油气管道在线检测中应用最广泛的无损检测技术,提出了一种去除漏磁数据中无缝管道噪声(SPN)和系统噪声的新算法.首先利用将小波变换和自适应滤波技术相结合而提出的新型小波域自适应滤波方法去除漏磁数据中的SPN,然后再利用小波系数去噪方法去除小波域自适应SPN消除系统输出漏磁数据中的系统噪声.实测漏磁数据所得结果表明,该算法具有良好的去噪效果,极大地提高了漏磁数据中缺陷信号的可检测性.

The Application of Wavelet Domain Adaptive Filtering and Coefficients De-noising with Wavelet Transform in Pipeline Magnetic Flux Leakage Data

Magnetic flux leakage(MFL) measurement is the most widely used non-destructive evaluation technique for in-service inspection of gas and oil pipelines.A new de-noising algorithm was presented for removing the seamless pipe noise(SPN) and the system noise contained in the MFL data.The algorithm utilizes the wavelet transform domain adaptive filtering method by combining the wavelet transform and the adaptive filtering technique to remove the SPN contained in the MFL data,and then exploits the coefficients de-noising approach with wavelet transform to cancel the system noise in the output MFL data of the wavelet transform domain adaptive SPN rejection system.The application results of the proposed algorithm to the MFL data from field tests were presented to demonstrate the effectiveness of the algorithm.